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  <table align="center" border="1">

    <tr bgcolor="lightblue">
      <th>Signature</th> <th>Description</th> <th>Parameters</th>
    </tr>
    <tr bgcolor="lightgrey">
      <td bgcolor="maroon"> <font color="white">
        <PRE><B>#include &lt;DataFrame/DataFrameTransformVisitors.h&gt;

template&lt;typename T, typename I = unsigned long&gt;
struct ExpoSmootherVisitor;

// -------------------------------------

template&lt;typename T, typename I = unsigned long&gt;
using exs_v = ExpoSmootherVisitor&lt;T, I&gt;;
        </B></PRE></font>
      </td>
      <td>
        This is a “single action visitor”, meaning it is passed the whole data vector in one call and you must use the single_act_visit() interface.<BR><BR>
        This is a transformer visitor. It means the column(s) passed to this visitor is not read-only and its values may change<BR><BR>
        This functor does exponential smoothing of the time-series by<BR>
        <I>Y<sub>0</sub> = X<sub>0</sub></I><BR>
        <I>Y<sub>t</sub> = aX<sub>t</sub> + (1 - a)Y<sub>t-1</sub></I><BR>
        <I>a</I> is the smoothing factor, and  0 < a < 1. Factor of 1 will not change the data.
        <I>
        <PRE>
    explicit
    ExpoSmootherVisitor(std::size_t data_smoothing_factor,
                        // You can do multiple smoothing in one call
                        std::size_t repeat_count = 1);
        </PRE>
        </I>
      </td>
      <td width="12%">
        <B>T</B>: Column data type.<BR>
        <B>I</B>: Index type.
      </td>
    </tr>

    <tr bgcolor="lightgrey">
      <td bgcolor="maroon"> <font color="white">
        <PRE><B>#include &lt;DataFrame/DataFrameTransformVisitors.h&gt;

template&lt;typename T, typename I = unsigned long&gt;
struct HWExpoSmootherVisitor;

// -------------------------------------

template&lt;typename T, typename I = unsigned long&gt;
using hwexp_v = HWExpoSmootherVisitor&lt;T, I&gt;;
        </B></PRE></font>
      </td>
      <td>
        This is a “single action visitor”, meaning it is passed the whole data vector in one call and you must use the single_act_visit() interface.<BR><BR>
        This is a transformer visitor. It means the column(s) passed to this visitor is not read-only and its values may change<BR><BR>
        This functor does double exponential smoothing by Holt-Winters method. The advantage for this over the above visitor is that HW takes care of trends in the data<BR>
        <I>
        Y<sub>0</sub> = X<sub>0</sub><BR>
        B<sub>0</sub> = X<sub>1</sub> - X<sub>0</sub><BR>
        </I>
        And for t > 0:<BR>
        <I>
        Y<sub>t</sub> = aX<sub>t</sub> + (1 - a) (Y<sub>t-1</sub> + B<sub>t-1</sub>)<BR>
        B<sub>t</sub> = b(Y<sub>t</sub> - Y<sub>t-1</sub>) + (1 - b)B<sub>t-1</sub><BR>
        </I>
        where a is the data smoothing factor, 0 < a < 1, and b is the trend smoothing factor, 0 < b < 1
        <I>
        <PRE>
    HWExpoSmootherVisitor(std::size_t data_smoothing_factor,
                          std::size_t trend_smoothing_factor);
        </PRE>
        </I>
      </td>
      <td width="12%">
        <B>T</B>: Column data type.<BR>
        <B>I</B>: Index type.
      </td>
    </tr>

  </table>

<pre style='color:#000000;background:#ffffff;'><span style='color:#800000; font-weight:bold; '>static</span> <span style='color:#800000; font-weight:bold; '>void</span> test_ExpoSmootherVisitor<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span>  <span style='color:#800080; '>{</span>

    <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>cout</span> <span style='color:#808030; '>&lt;</span><span style='color:#808030; '>&lt;</span> <span style='color:#800000; '>"</span><span style='color:#0f69ff; '>\n</span><span style='color:#0000e6; '>Testing ExpoSmootherVisitor{  } ...</span><span style='color:#800000; '>"</span> <span style='color:#808030; '>&lt;</span><span style='color:#808030; '>&lt;</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>endl</span><span style='color:#800080; '>;</span>

    <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>unsigned</span> <span style='color:#800000; font-weight:bold; '>long</span><span style='color:#800080; '>></span>  idx <span style='color:#808030; '>=</span>
        <span style='color:#800080; '>{</span> <span style='color:#008c00; '>123450</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123451</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123452</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123453</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123454</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123455</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123456</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123457</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123458</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123459</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123460</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123461</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123462</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123466</span><span style='color:#808030; '>,</span>
          <span style='color:#008c00; '>123467</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123468</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123469</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123470</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123471</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123472</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123473</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123467</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123468</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123469</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123470</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123471</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123472</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123473</span><span style='color:#808030; '>,</span>
          <span style='color:#008c00; '>123467</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123468</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123469</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123470</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123471</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123472</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123473</span><span style='color:#808030; '>,</span>
        <span style='color:#800080; '>}</span><span style='color:#800080; '>;</span>
    <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span>         d1 <span style='color:#808030; '>=</span>
        <span style='color:#800080; '>{</span> <span style='color:#008000; '>2.5</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.45</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.65</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.1</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.1</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.87</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.98</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.34</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.56</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>12.34</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.3</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.34</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.9</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.387</span><span style='color:#808030; '>,</span>
          <span style='color:#008000; '>0.123</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.06</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.65</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.03</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.4</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.0</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.59</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.125</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.9</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.68</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.0045</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>50.8</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.0</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.78</span><span style='color:#808030; '>,</span>
          <span style='color:#008000; '>0.48</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.99</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.97</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.03</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>8.678</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.4</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.59</span><span style='color:#808030; '>,</span>
        <span style='color:#800080; '>}</span><span style='color:#800080; '>;</span>
    <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span>         d1_copy <span style='color:#808030; '>=</span> d1<span style='color:#800080; '>;</span>
    MyDataFrame                 df<span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>load_data<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>move</span><span style='color:#808030; '>(</span>idx<span style='color:#808030; '>)</span><span style='color:#808030; '>,</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span>make_pair<span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> d1<span style='color:#808030; '>)</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    MyDataFrame df2 <span style='color:#808030; '>=</span> df<span style='color:#800080; '>;</span>

    ExpoSmootherVisitor<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span> es_v1<span style='color:#808030; '>(</span><span style='color:#008c00; '>1</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>single_act_visit<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> es_v1<span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>const</span> <span style='color:#800000; font-weight:bold; '>auto</span>  <span style='color:#808030; '>&amp;</span>col1 <span style='color:#808030; '>=</span> df<span style='color:#808030; '>.</span>get_column<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>for</span> <span style='color:#808030; '>(</span><span style='color:#603000; '>size_t</span> idx <span style='color:#808030; '>=</span> <span style='color:#008c00; '>0</span><span style='color:#800080; '>;</span> idx <span style='color:#808030; '>&lt;</span> col1<span style='color:#808030; '>.</span>size<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span> <span style='color:#808030; '>+</span><span style='color:#808030; '>+</span>idx<span style='color:#808030; '>)</span>
       assert<span style='color:#808030; '>(</span><span style='color:#603000; '>fabs</span><span style='color:#808030; '>(</span>col1<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> d1_copy<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.00001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    ExpoSmootherVisitor<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span> es_v2<span style='color:#808030; '>(</span><span style='color:#008000; '>0.3</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>single_act_visit<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> es_v2<span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>auto</span>    actual2 <span style='color:#808030; '>=</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span> <span style='color:#800080; '>{</span>
        <span style='color:#008000; '>2.5</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.485</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.22</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.185</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.4</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.209</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.603</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.788</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.706</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>2.61</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>7.948</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.508</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.808</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.2139</span><span style='color:#808030; '>,</span>
        <span style='color:#008000; '>0.3078</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.4041</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.547</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.154</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.541</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.02</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.523</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.4505</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.6575</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.126</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.12535</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>16.6431</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>35.26</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.466</span><span style='color:#808030; '>,</span>
        <span style='color:#008000; '>0.69</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.933</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.102</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.37</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>3.3244</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>5.6546</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.503</span>
    <span style='color:#800080; '>}</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>for</span> <span style='color:#808030; '>(</span><span style='color:#603000; '>size_t</span> idx <span style='color:#808030; '>=</span> <span style='color:#008c00; '>0</span><span style='color:#800080; '>;</span> idx <span style='color:#808030; '>&lt;</span> col1<span style='color:#808030; '>.</span>size<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span> <span style='color:#808030; '>+</span><span style='color:#808030; '>+</span>idx<span style='color:#808030; '>)</span>
       assert<span style='color:#808030; '>(</span><span style='color:#603000; '>fabs</span><span style='color:#808030; '>(</span>col1<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> actual2<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.0001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>get_column<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>=</span> d1_copy<span style='color:#800080; '>;</span>

    ExpoSmootherVisitor<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span> es_v3<span style='color:#808030; '>(</span><span style='color:#008000; '>0.8</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>single_act_visit<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> es_v3<span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>auto</span>    actual3 <span style='color:#808030; '>=</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span> <span style='color:#800080; '>{</span>
        <span style='color:#008000; '>2.5</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.46</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.83</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.41</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.9</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.276</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.158</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.468</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.316</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>9.56</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.628</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.188</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.588</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.0704</span><span style='color:#808030; '>,</span>
        <span style='color:#008000; '>0.1758</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.8726</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.308</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.494</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.726</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.72</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.272</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.218</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.545</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.164</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.4676</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>41.0409</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>9.36</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.424</span><span style='color:#808030; '>,</span>
        <span style='color:#008000; '>0.54</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.688</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.378</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.63</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>7.1484</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.6156</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.992</span>
    <span style='color:#800080; '>}</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>for</span> <span style='color:#808030; '>(</span><span style='color:#603000; '>size_t</span> idx <span style='color:#808030; '>=</span> <span style='color:#008c00; '>0</span><span style='color:#800080; '>;</span> idx <span style='color:#808030; '>&lt;</span> col1<span style='color:#808030; '>.</span>size<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span> <span style='color:#808030; '>+</span><span style='color:#808030; '>+</span>idx<span style='color:#808030; '>)</span>
       assert<span style='color:#808030; '>(</span><span style='color:#603000; '>fabs</span><span style='color:#808030; '>(</span>col1<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> actual3<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.0001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    ExpoSmootherVisitor<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span> es_v3_4 <span style='color:#808030; '>(</span><span style='color:#008000; '>0.8</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>4</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
    <span style='color:#800000; font-weight:bold; '>const</span> <span style='color:#800000; font-weight:bold; '>auto</span>                  <span style='color:#808030; '>&amp;</span>col21 <span style='color:#808030; '>=</span> df2<span style='color:#808030; '>.</span>get_column<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    df2<span style='color:#808030; '>.</span>single_act_visit<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> es_v3_4<span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>auto</span>    actual4 <span style='color:#808030; '>=</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span> <span style='color:#800080; '>{</span>
        <span style='color:#008000; '>2.5</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.47952</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.77968</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.27248</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.67824</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.261712</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.9932</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.799584</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.97488</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>4.33518</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>3.8625</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.05213</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.877632</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.632813</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.087968</span><span style='color:#808030; '>,</span>
        <span style='color:#008000; '>0.494816</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.193696</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.731832</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.922821</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.051104</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.055568</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.152752</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.895104</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.532416</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.838499</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>21.5731</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>20.6916</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>7.763</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.66618</span><span style='color:#808030; '>,</span>
        <span style='color:#008000; '>1.1872</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.509888</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.343776</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>3.87912</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>3.11763</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.43558</span>
    <span style='color:#800080; '>}</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>for</span> <span style='color:#808030; '>(</span><span style='color:#603000; '>size_t</span> idx <span style='color:#808030; '>=</span> <span style='color:#008c00; '>0</span><span style='color:#800080; '>;</span> idx <span style='color:#808030; '>&lt;</span> col21<span style='color:#808030; '>.</span>size<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span> <span style='color:#808030; '>+</span><span style='color:#808030; '>+</span>idx<span style='color:#808030; '>)</span>
       assert<span style='color:#808030; '>(</span><span style='color:#603000; '>fabs</span><span style='color:#808030; '>(</span>col21<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> actual4<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.0001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
<span style='color:#800080; '>}</span>

<span style='color:#696969; '>// -----------------------------------------------------------------------------</span>

<span style='color:#800000; font-weight:bold; '>static</span> <span style='color:#800000; font-weight:bold; '>void</span> test_HWExpoSmootherVisitor<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span>  <span style='color:#800080; '>{</span>

    <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>cout</span> <span style='color:#808030; '>&lt;</span><span style='color:#808030; '>&lt;</span> <span style='color:#800000; '>"</span><span style='color:#0f69ff; '>\n</span><span style='color:#0000e6; '>Testing HWExpoSmootherVisitor{  } ...</span><span style='color:#800000; '>"</span> <span style='color:#808030; '>&lt;</span><span style='color:#808030; '>&lt;</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>endl</span><span style='color:#800080; '>;</span>

    <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>unsigned</span> <span style='color:#800000; font-weight:bold; '>long</span><span style='color:#800080; '>></span>  idx <span style='color:#808030; '>=</span>
        <span style='color:#800080; '>{</span> <span style='color:#008c00; '>123450</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123451</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123452</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123453</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123454</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123455</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123456</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123457</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123458</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123459</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123460</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123461</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123462</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123466</span><span style='color:#808030; '>,</span>
          <span style='color:#008c00; '>123467</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123468</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123469</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123470</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123471</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123472</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123473</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123467</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123468</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123469</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123470</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123471</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123472</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123473</span><span style='color:#808030; '>,</span>
          <span style='color:#008c00; '>123467</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123468</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123469</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123470</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123471</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123472</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>123473</span><span style='color:#808030; '>,</span>
        <span style='color:#800080; '>}</span><span style='color:#800080; '>;</span>
    <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span>         d1 <span style='color:#808030; '>=</span>
        <span style='color:#800080; '>{</span> <span style='color:#008000; '>2.5</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.45</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.65</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.1</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.1</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.87</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.98</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.34</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.56</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>12.34</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.3</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.34</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.9</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.387</span><span style='color:#808030; '>,</span>
          <span style='color:#008000; '>0.123</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.06</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.65</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.03</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.4</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.0</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.59</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.125</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.9</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.68</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.0045</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>50.8</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.0</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.78</span><span style='color:#808030; '>,</span>
          <span style='color:#008000; '>0.48</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.99</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.97</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.03</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>8.678</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.4</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.59</span><span style='color:#808030; '>,</span>
        <span style='color:#800080; '>}</span><span style='color:#800080; '>;</span>
    <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span>         d1_copy <span style='color:#808030; '>=</span> d1<span style='color:#800080; '>;</span>
    MyDataFrame                 df<span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>load_data<span style='color:#808030; '>(</span><span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>move</span><span style='color:#808030; '>(</span>idx<span style='color:#808030; '>)</span><span style='color:#808030; '>,</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span>make_pair<span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> d1<span style='color:#808030; '>)</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    HWExpoSmootherVisitor<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span>   es_v1<span style='color:#808030; '>(</span><span style='color:#008c00; '>1</span><span style='color:#808030; '>,</span> <span style='color:#008c00; '>1</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>single_act_visit<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> es_v1<span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>const</span> <span style='color:#800000; font-weight:bold; '>auto</span>  <span style='color:#808030; '>&amp;</span>col1 <span style='color:#808030; '>=</span> df<span style='color:#808030; '>.</span>get_column<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>for</span> <span style='color:#808030; '>(</span><span style='color:#603000; '>size_t</span> idx <span style='color:#808030; '>=</span> <span style='color:#008c00; '>0</span><span style='color:#800080; '>;</span> idx <span style='color:#808030; '>&lt;</span> col1<span style='color:#808030; '>.</span>size<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span> <span style='color:#808030; '>+</span><span style='color:#808030; '>+</span>idx<span style='color:#808030; '>)</span>
       assert<span style='color:#808030; '>(</span><span style='color:#603000; '>fabs</span><span style='color:#808030; '>(</span>col1<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> d1_copy<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.00001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    HWExpoSmootherVisitor<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span>   es_v2<span style='color:#808030; '>(</span><span style='color:#008000; '>0.3</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.4</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>single_act_visit<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> es_v2<span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>auto</span>    actual2 <span style='color:#808030; '>=</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span> <span style='color:#800080; '>{</span>
        <span style='color:#008000; '>2.5</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.45</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.185</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>2.354</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.6674</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.64944</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.17034</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.879202</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.581521</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>2.34309</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>11.6799</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>3.36809</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.431147</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.42459</span><span style='color:#808030; '>,</span>
        <span style='color:#008000; '>0.821747</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.638548</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.950029</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.0829826</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.14921</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.111474</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.969884</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.627569</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.633542</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.60863</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.307475</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>17.1351</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>49.2179</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>6.59525</span><span style='color:#808030; '>,</span>
        <span style='color:#808030; '>-</span><span style='color:#008000; '>2.48915</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.05849</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.329906</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.66206</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>3.10917</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>7.6669</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>2.11746</span><span style='color:#808030; '>,</span>
    <span style='color:#800080; '>}</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>for</span> <span style='color:#808030; '>(</span><span style='color:#603000; '>size_t</span> idx <span style='color:#808030; '>=</span> <span style='color:#008c00; '>0</span><span style='color:#800080; '>;</span> idx <span style='color:#808030; '>&lt;</span> col1<span style='color:#808030; '>.</span>size<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span> <span style='color:#808030; '>+</span><span style='color:#808030; '>+</span>idx<span style='color:#808030; '>)</span>
       assert<span style='color:#808030; '>(</span><span style='color:#603000; '>fabs</span><span style='color:#808030; '>(</span>col1<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> actual2<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.0001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>get_column<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>=</span> d1_copy<span style='color:#800080; '>;</span>

    HWExpoSmootherVisitor<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span>   es_v3<span style='color:#808030; '>(</span><span style='color:#008000; '>0.8</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.8</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    df<span style='color:#808030; '>.</span>single_act_visit<span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span><span style='color:#808030; '>(</span><span style='color:#800000; '>"</span><span style='color:#0000e6; '>dbl_col</span><span style='color:#800000; '>"</span><span style='color:#808030; '>,</span> es_v3<span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>auto</span>    actual3 <span style='color:#808030; '>=</span> <span style='color:#666616; '>std</span><span style='color:#800080; '>::</span><span style='color:#603000; '>vector</span><span style='color:#800080; '>&lt;</span><span style='color:#800000; font-weight:bold; '>double</span><span style='color:#800080; '>></span> <span style='color:#800080; '>{</span>
        <span style='color:#008000; '>2.5</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.45</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.84</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.068</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.7836</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.13928</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.60586</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.415171</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.20303</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>9.38739</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>2.81748</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>2.0925</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>1.6295</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.3283</span><span style='color:#808030; '>,</span>
        <span style='color:#008000; '>0.49014</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.893228</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.153954</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.25121</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.10624</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.904752</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.0110497</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.42021</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.51104</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.113208</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.11024</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>41.3989</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>17.2389</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>6.28822</span><span style='color:#808030; '>,</span>
        <span style='color:#808030; '>-</span><span style='color:#008000; '>0.517644</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.42847</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.188306</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>0.194339</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>7.38127</span><span style='color:#808030; '>,</span> <span style='color:#008000; '>1.88585</span><span style='color:#808030; '>,</span> <span style='color:#808030; '>-</span><span style='color:#008000; '>0.366429</span>
    <span style='color:#800080; '>}</span><span style='color:#800080; '>;</span>

    <span style='color:#800000; font-weight:bold; '>for</span> <span style='color:#808030; '>(</span><span style='color:#603000; '>size_t</span> idx <span style='color:#808030; '>=</span> <span style='color:#008c00; '>0</span><span style='color:#800080; '>;</span> idx <span style='color:#808030; '>&lt;</span> col1<span style='color:#808030; '>.</span>size<span style='color:#808030; '>(</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span> <span style='color:#808030; '>+</span><span style='color:#808030; '>+</span>idx<span style='color:#808030; '>)</span>
       assert<span style='color:#808030; '>(</span><span style='color:#603000; '>fabs</span><span style='color:#808030; '>(</span>col1<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span> <span style='color:#808030; '>-</span> actual3<span style='color:#808030; '>[</span>idx<span style='color:#808030; '>]</span><span style='color:#808030; '>)</span> <span style='color:#808030; '>&lt;</span> <span style='color:#008000; '>0.0001</span><span style='color:#808030; '>)</span><span style='color:#800080; '>;</span>
<span style='color:#800080; '>}</span>
</pre>
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